Data Science Projects for Freelancers

I need 1500 images annotated for object detection. The annotations will be used to train machine learning models.

Requirements:
- Annotate images with bounding boxes around people / occupied seats for obb models , roatation included for leaned persons
- Ensure accuracy and consistency in annotations.
- Use annotation tools simple annotation tool ceated by me specifically for this

Ideal Skills:
- Experience in image annotation.
- Attention to detail and precision.
- Familiarity with object detection concepts.

Looking forward to your bids!

Skills: Python, Matlab and Mathematica, Machine Learning (ML), Imaging, Data Science, Image Processing, Computer Vision, Deep Learning, Image Recognition, Object Detection

Description:
I'm building the backend for an app called "mumbl" — transforms vocal recordings (mumbles, mumbled melodies) into lyrics + transcriptions. You’ll work with an existing FastAPI repo that includes Whisper integration and tests. Tasks include:

• Complete whisper transcription pipeline
• Add audio analysis (key/tempo)
• Integrate LLM to generate lyrics
• Build clean API endpoints
• Add tests

Deliverables:
• Working /transcribe, /analyze_audio, /generate_lyrics
• Unit tests
• Deployment guidance

Please include relevant experience with audio processing apps.

Advanced Full-Stack Developer (Data & High-Scale Systems)
Salary: 20M IDR/month
Contract: Full-time

📌 Role Overview

We are looking for an advanced Full-Stack Developer with strong experience in data-heavy systems, automation, and high-volume APIs.
You will work on multiple real-world projects, handling millions of data points, building internal tools, dashboards, and scalable infrastructures.
This is a hands-on engineering role, with growth potential toward a future technical lead / manager position.

🧠 Responsibilities

Build and optimize systems handling large volumes of data and API requests
Develop and maintain backend & frontend features
Create automation scripts and internal tools
Work on data processing, scoring, analytics and performance tracking
Build dashboards and interfaces using React
Improve scalability, performance, reliability, and structure
Communicate clearly with non-technical team members
Be proactive in architecture and technical decisions

🛠️ Tech Stack

Node.js / NestJS
JavaScript
React
PostgreSQL
Prisma
Data pipelines, API optimization, automation workflows

Nice-to-have (not mandatory):
Python for data processing
Basic ML / prediction logic (rules-based or simple models)

🎯 Requirements

3–5+ years as a Full-Stack Developer
Strong experience with data-heavy applications
Comfortable with multi-project environments
Autonomous, reliable, execution-oriented
Good communication skills
Able to take ownership and propose solutions
Comfortable with SEO and using IA
Must be able to work in Seminyak, Bali

💡 What We Offer

20M IDR / month (possibly to increase in the future)
Long-term, stable position
Multi-project, real-scale environment
Direct collaboration with the founder
Growth path toward technical leadership

🖋️ Can you answer these questions please :

Are you currently living in Bali or able to work on-site in Seminyak immediately?
Describe one project where you handled large datasets or high API volume.
What is your strongest skill: backend, frontend, or data processing?
Have you ever mentored or led other developers?

I need help analyzing spatial transcriptomics data from three lung biopsies of patients with a specific lung disease.

The analysis should include:
- Differential expression analysis
- Cell type identification
- Spatial patterning analysis

I have specific cell markers and reference datasets that I would like to use.

Please use Seurat for this analysis.

Ideal Skills and Experience:
- Expertise in spatial transcriptomics
- Proficiency in Seurat
- Experience with differential expression, cell type identification, and spatial patterning analysis
- Strong background in bioinformatics and transcriptomics

Skills: Matlab and Mathematica, Statistics, Statistical Analysis, Data Science, Data Visualization, Data Analysis, Bioinformatics, Biostatistics

I have a CSV file that contains categorical information on concrete mix ingredients and curing ages, and I need a regression model that can predict compressive strength with solid accuracy. You will start with exploratory data analysis, handle any necessary feature engineering to make the categorical inputs usable, train and validate several algorithms, and finally settle on the one that delivers the best generalisation performance.

Please work in Python and share fully commented notebooks or scripts so I can reproduce every step, from loading the raw CSV to exporting the final model. Key metrics such as MAE, RMSE, and R² on a held-out test set should be reported, and the final model object saved for later deployment.

Deliverables
• Cleaned and engineered dataset (CSV or pickle)
• Reproducible code/notebook with clear explanations
• Performance report with plots and metrics
• Serialized final regression model ready for inference

Skills: Python, Data Processing, Machine Learning (ML), Data Science, Scikit Learn, NumPy, Data Visualization, Data Analysis, Pandas, Regression Analysis

Scope of Work

AI Workflow (Reliability & Production):
End-to-end review of data acquisition and processing pipelines, identification of failure points, and implementation in production of corrective measures to secure flows and reduce errors. This includes content generation, email sending, and website publication.

Forum:
Functional and technical review followed by production implementation of improvements covering user interactions (comments, replies, tracking), moderation, and user management.

User Journey:
Analysis of the end-to-end user journey (signup, navigation, payment, retention) and deployment of optimizations to remove friction points.

Emailing:
Review of content and transactional emails (signup, payment, notifications), followed by implementation of improvements on deliverability, message clarity, and journey consistency.

Advertising / Ads:
Review and production setup of advertising and tracking mechanisms (display, tracking accuracy, consistency with UX), with a focus on data reliability and non-degradation of the user journey.

Front-end:
Implementation of targeted improvements to ergonomics, readability, and visual consistency (non-priority but desirable).

Premium Content Production:
Recommendations and implementation regarding methodology, content structure, process redesign if needed, and data acquisition/exploitation to increase the value of premium articles.

Technology Stack
Python (automation, data pipelines, production scripts) and Next.js (front-end and full-stack implementation).

Execution Plan (to be adjusted together)

Onboarding – 1 week
Access handover, platform onboarding, understanding of architecture, workflows, and usage. Review call at the end of the phase.

Production – 1 month
Implementation of fixes, optimizations, and hardening in production, with documentation. Weekly check-ins and ad-hoc communication if blocking issues arise.

Follow-up
Ongoing steering, post-production adjustments, fixes, and support.

We are seeking a talented creative writer who possesses a strong statistical background. Your task will be to develop benchmarks that allow for the effective evaluation of large language model (LLM) outputs. This role combines creativity with analytical skills to ensure thorough and engaging benchmark creation. You will work closely with our data science team to establish criteria and metrics that enhance LLM performance assessment. If you have a knack for storytelling paired with statistical insight, we want to hear from you!

• Describe your recent experience with similar projects

Title
Full-Stack Developer for AI Product Image Generator MVP

Description
We need a developer to build a simple AI SaaS website where users can upload a product image, generate a set of e-commerce product images, and download results.
Features: user login, credit system, Stripe payment, async backend, cloud deployment.
AI model is provided — integration only.
MVP, clean and simple.

We are looking for a skilled AI developer to create a predictive model by utilizing existing solutions that identifies companies likely to expand into new countries within the next 12 months. The model should leverage public data sources and apply suitable machine learning algorithms to analyze trends and patterns. The ideal candidate will possess a strong background in data science and machine learning to deliver accurate and actionable insights. If you have experience in AI development and predictive analytics, we would love to hear from you.

• Describe your recent experience with similar projects

we need github starts
We are seeking a skilled data analyst to help us analyze GitHub repositories based on their star counts. The ideal candidate will work closely with our team to extract, process, and visualize data regarding repository popularity. Your insights will drive our development strategy, so proficiency in data analysis tools and GitHub APIs is essential. If you have a passion for data and experience in extracting meaningful metrics from GitHub, we want to hear from you!

Needs to hire 20 Freelancers

We are seeking highly skilled Biomedical Informatics Subject Matter Experts (SMEs) to join our team in developing rigorous, high-quality evaluation questions designed to assess and challenge advanced AI models. The primary objective is to create benchmark questions that test the boundaries of AI capabilities across diverse bioinformatics domains.
This role requires deep technical expertise combined with the ability to craft precise, unambiguous questions with well-defined evaluations. The ideal candidate will possess not only strong theoretical knowledge but also practical experience in designing assessment materials that have deterministic, verifiable outcomes.

Responsibilities:
● Design and develop challenging bioinformatics coding questions that push the limits of AI model capabilities.
● Create automated, coding-based evaluations with unit tests that objectively verify correctness.
● Build comprehensive evaluation rubrics with 7–10 distinct criteria for each bioinformatics question.
● Ensure every question is self-contained, well-defined, and completely unambiguous, including all domain rules and edge cases.
● Develop problems where there is exactly one correct answer or outcome that can be deterministically validated.
● Translate theoretical bioinformatics concepts into concrete, measurable outputs.
● Enforce performance requirements with explicit constraints and tests to prevent inefficient or brute-force solutions.

Required Qualifications:

Educational Background

● Master's degree of experience in biomedical data processing and interpretation.
● Ongoing PhD with 3+ years of experience in biomedical data processing and interpretation.
● PhD (completed) in Biomedical Informatics, Bioinformatics, Computational Biology or a closely related field (preferred).

Domain Expertise Requirements

Candidates must demonstrate deep, expert-level knowledge in at least TWO (2) of the following five core bioinformatics domains:

1. Biomedical Image Processing
● Processing of Radiology imaging: CT, MRI, PET/SPECT, Ultrasound imaging
● Automating cell counting, identifying cell types, and analyzing tissue structures in pathology slides
● Computational segmentation and boundary inference
● Medical image formation, reconstruction & enhancement
● Noise modeling and statistical denoising
● Image sampling theory and resolution limits
● Intensity standardization and harmonization
● Geometric transformations and spatial calibration
● Multi-modal image registration and alignment
● Morphological and topological shape analysis
● Quantitative imaging feature extraction
● Fusing data from different modalities (MRI, PET, Genomics) for a comprehensive view to tailor treatments
● pattern recognition and predictive modeling

2. Biomedical Signal Processing
● Cardiovascular/hemodynamic signals (ECG, PPG, BP, HRV, etc)
● Neural/brain electrical signals (EEG, EP/ERP; seizure/cognitive analysis)
● Neuromuscular/motor signals (EMG, motor unit decomposition; prosthetics/rehab)
● Ocular/visual system signals (EOG, blink/saccade analysis)
● Respiratory signals (airflow, effort; sleep/disordered breathing)
● Nonlinear, Statistical, and Adaptive Signal Analysis
● Multichannel, Spatial, and Connectivity Signal Analysis
● Machine Learning and Data‑Driven Biomedical Signal Analysis
● Clinical Monitoring, Wearable, and Translational Signal Processing

3. Molecular & Omics based Personalized Medicine
● Omics based risk / disease prediction (GWAS, PRS, bulk, single‑cell RNA‑seq, proteins / metabolite signatures associated with diseases)
● Risk Prediction and Prognosis Modeling
● Molecular patient subtyping
● Liquid Biopsy and Circulating Biomarkers (ctDNA, cfRNA/miRNA, MRD, etc.)
● Causal Inference & Mechanistic Inference (ATE/CATE, Trial emulation and counterfactual modeling)
● Cross‑modal data fusion (omics + EHR + imaging / signals)
● Longitudinal Patient Modeling and Disease Progression
● Patient Stratification and Subtyping (molecular subtypes, endotypes)
● Electronic Health Records and Clinical Data Science

4. Drug Discovery & Repurposing
● Treatment response prediction
● Structure-based drug design (Molecular docking, binding site analysis, Virtual screening workflow)
● Protein structure analysis (PDB/mmCIF handling)
● Chemoinformatics ( Ligand-based screening, molecular fingerprinting, 2D/3D data handling and chemical space analysis)
● QSAR & ADMET Modeling
● Drug–target interaction prediction
● Drug sensitivity prediction in disease models
● Repurposing via omics/network associations
● Predictive Modeling for Drug Discovery
Molecular Dynamics Simulation of Biomolecules (QM, DFT, stability, reactivity, PCA analysis )

5. Software / Utilities
● Tool installation & environment management (docker/conda/pip)
● Format conversion/validation (FASTA/FASTQ, BAM/VCF, PDB)
● GUI-driven analysis workflows (step-by-step runs)
● Workflow automation (scripts wrapping GUI tools)
● Visualization tools (genome browsers, 3D viewers)
● Container/VM execution and troubleshooting
● Batch processing and report generation
● Pipeline interoperability checks
● Reproducibility packaging (configs, manifests)
● Debugging typical bioinformatics tool errors

6. Regulatory Science and Clinical Policies
● FDA/EMA regulatory pathways
● Clinical Practice Guidelines & Standards of Care (e.g., NCCN, AHA, etc.)
● Diagnostic Biomarker & Therapeutic Use Constraints
● Medical Scenario Reasoning (case vignettes, Differential diagnosis)
● Data & Content Compliance
● Ethical Use, Safety, and Harm Prevention
● Model Use Governance & Auditability
● Policy‑Aligned Language & Communication
● Clinical validation and cohort generalization
● Privacy‑preserving learning

Perks of Freelancing With Jupiter AI labs:
● Work in a fully remote environment.
● Opportunity to work on cutting-edge AI projects with leading LLM companies.
● Potential for contract extension based on performance and project needs.

Full time dedication (40 hours / week)
Requires 4 hours overlap with PST (Pacific Standard Time)
Opportunity- Full Time, 4 hours 7-11 pm IST is mandatory time , rest 4 hrs is optional /flexible
=Paid interview of 90 min
Hourly rate: $8 USD or monthly pay as per consensus
Are you available from fixed pay of 173 hrs at 8 USD /hr for 8 hrs daily for one month cycle.
If yes the payment will be in this way, if you work from 1 Jan to 31 Jan , our system pay by 17-18 Feb as per upwork payment , and similar the cycle continue every month

• Do you have Proven track record in Biomedical Informatics, Bioinformatics, Computational Biology PHD /Master or pursuing PHD with 3+ year exp in this space, if yes pls confirm.
• Can you pass the assessment test with no llm/chatgpt help and it is will 12 hrs take home test , it will be a paid test if you pass , do you agree
• Do you agree to payment terms?

I run Techtutorialz.com and our learners are ready for the next round of live classes. The audience is already comfortable with the basics, so the material must challenge an intermediate crowd and help both freshers and working professionals sharpen their job-related skills.

What I need from you
• A detailed course outline (Python plus touches of AI, ML or GenAI where relevant) sent to training at techtutorialz.com
• Engaging, real-time sessions delivered online with clear explanations and hands-on coding demonstrations
• Practical mini–projects or exercises that reinforce each topic and can be reviewed in class
• Short assignments and quizzes that gauge progress between sessions
• Availability for Q&A support outside live hours

Session logistics, preferred tools (Zoom, Jupyter, VS Code, etc.) and the final timetable can be settled once I review your outline. Follow the link below to see our existing catalogue and tone:
https://techtutorialz.com/category/Training/

If you thrive on interactive teaching and can weave Python fundamentals into applied examples spanning data handling, automation or beginner-friendly machine learning workflows, drop me your syllabus and a brief trainer bio.

Skills: Python, Graphic Design, Software Architecture, Statistics, Software Development, Data Science, Data Visualization, Data Analysis, Training Development, Teaching/Lecturing

We are seeking an expert data scientist to conduct a 5-year temporal ice study. The project involves MGRS grid alignment and requires proficiency in TensorRT-optimized U-Net for image processing tasks. The ideal candidate will have experience with multi-GPU temporal sharding and pixel-level transition analysis. If you have a proven track record in these areas and a passion for data analysis, we want to hear from you!

We are seeking an experienced AI Engineering Bootcamp Professor to lead an intensive program aimed at equipping students with the necessary skills in artificial intelligence and machine learning. The ideal candidate will have a passion for teaching, a strong foundation in AI concepts, and hands-on experience with real-world projects. Responsibilities include creating curriculum, delivering lectures, and mentoring students. If you are enthusiastic about shaping the next generation of AI professionals, we want to hear from you!

This is a simple post, I am looking for someone who can write and build trading strategies for my tea to develop the algos and to work together on producing amazing profitable algorithms that will perform amazing and importantly out of all must be managing and be consistant and always working on it.

I need a complete, beginner-friendly training program that takes absolute newcomers and turns them into job-ready practitioners across three pillars of modern machine learning: Natural Language Processing, Computer Vision, and Predictive Analytics. Everything must be delivered through live online sessions so students can ask questions in real time and work through hands-on exercises as a group.

Here’s what I’m expecting from you:

• A structured curriculum that steadily builds from zero knowledge to employment-level competence in each focus area.
• Live session slide decks, annotated notebooks or scripts, and any datasets you plan to use, shared ahead of each class.
• Practical projects after every major module so learners leave with portfolio-worthy work.
• Brief quizzes or checkpoints to confirm concepts have landed.
• Recordings of the sessions for later review.

Plan to weave in popular toolchains—think Python, scikit-learn, TensorFlow or PyTorch, Jupyter, plus the usual NLP and vision libraries—while keeping explanations clear, jargon-light, and immediately actionable. By the end, attendees should feel confident discussing model choices, training and evaluating them, and deploying simple prototypes.

If you have run similar live cohorts before, let me know the approximate class size you’re comfortable with and share a sample agenda or feedback from past participants. I’m ready to start as soon as the outline and calendar are agreed.

Skills: Java, Python, Software Architecture, Machine Learning (ML), Data Science, Computer Vision, Predictive Analytics, Natural Language Processing

I am looking for an experienced Machine Learning / Data Science expert to support me with my dissertation project.

The project focuses on machine learning models for detection/classification using labelled datasets. I need support from start to finish, including:

🔹 Scope of Work
• Understanding the dissertation requirements and research objectives
• Assisting with data preprocessing and feature engineering
• Designing, training, and evaluating machine learning models
• Comparing models and improving performance
• Helping interpret results in an academic/research context
• Supporting the writing of the dissertation report (methodology, experiments, results, discussion – no plagiarism)
• Guidance on best practices, structure, and academic standards

🔹 Key Requirements
• Strong background in Machine Learning (supervised learning, classification, model evaluation)
• Experience working with labelled datasets
• Proficiency in Python (NumPy, Pandas, scikit-learn, and/or PyTorch / TensorFlow)
• Experience with research projects or academic dissertations
• Ability to clearly explain concepts and decisions
• Good communication skills

🔹 Working Style
• I am specifically looking for someone I can meet with regularly (weekly or more if needed) to discuss progress, decisions, and next steps
• Sessions can be via Zoom/Google Meet
• Collaborative approach, I want to understand the work, not just receive code
• Long-term collaboration until the dissertation is completed

🔹 Important Notes
• This is academic support, not ghostwriting
• All work must be original and plagiarism-free
• Experience helping students with dissertations or research projects is a big plus

If this sounds like a good fit, please include:
• Your relevant experience with ML and academic projects
• Examples of similar projects you’ve worked on
• Your availability for regular meetings

Position Overview
We are seeking a Machine Learning Engineer Consultant to spearhead the development and delivery of cutting-edge AI solutions, with a specialized focus on Agentic AI. This is a high-impact, hands-on role where you will act as both a strategic technical leader and a primary individual contributor.
You will be responsible for shipping production-grade ML systems while mentoring and enabling two Junior ML Engineers. Your mission is to balance rapid technical execution with the development of engineering standards (SOPs) and documentation that will scale our AI Solutions unit. The ideal candidate is a technical powerhouse who can unblock a team, interface with senior stakeholders, and navigate the complexities of enterprise-grade AI deployment.

Key Responsibilities
Technical Leadership & Delivery: Lead the end-to-end delivery of AI solutions from initial discovery through deployment. Maintain a high "hands-on" ratio, coding and debugging alongside the team to ensure enterprise-grade performance.
Agentic AI & Model Optimization: Design and implement autonomous decision-making systems and multi-turn workflows. Drive model fine-tuning and optimization for scalability and ROI.
Operational Excellence: Build the unit's "playbook" by developing SOPs, technical documentation, and engineering standards to ensure repeatable success.
Mentorship: Actively develop two Junior ML Engineers through regular code reviews, technical guidance, and career coaching to build a high-performing engineering culture.
Consulting & Stakeholder Management: Represent the firm in client workshops and engagements. Translate complex technical architectures into strategic value for non-technical senior stakeholders.
Innovation: Stay at the forefront of AI/ML advancements (e.g., Generative AI, Speech processing) to ensure our techniques remain state-of-the-art.

Qualifications
Education & Experience
Academic: Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field (Master’s preferred).
Experience: 3+ years of professional experience in Machine Learning Engineering, specifically deploying multiple production-grade models.
Context: Proven experience in enterprise-client-facing roles or within large-scale enterprise technical teams.

Technical Skills
Core Engineering: Mastery of Python or R and deep expertise in frameworks like PyTorch or TensorFlow.
Software Standards: Robust experience with Git-based version control, unit testing, and CI/CD pipelines.
Agentic AI: Proficient with LangChain (or similar frameworks) for workflow orchestration, LLM integration, and building autonomous agents.
Data & Science: Strong foundation in statistical analysis, hypothesis testing, and experimental design. Experience with Big Data (Spark, Hadoop) is a plus.
Speech & Audio (Plus): Familiarity with MT, STT, TTS, or speech libraries (Kaldi, HuggingFace Transformers) is highly regarded.

Core Competencies
Strategic Thinking: Ability to focus on unit economics and ROI-focused design.
Communication: Exceptional ability to bridge the gap between technical execution and business strategy.
Leadership Potential: Demonstrated aptitude for establishing standards and a clear trajectory toward senior leadership (e.g., CTO-level progression).

I’m putting together a roster of experienced trainers who can run end-to-end, instructor-led courses for our Indian corporate clients. The immediate need is for four subjects: Data Science, Digital Marketing, Project Management and AI.

Here’s what I expect from each trainer:
• Complete ownership of courseware – slide decks, hands-on labs, assessments and reference material must be ready to go.
• Classroom and/or live-virtual delivery inside India, typically in 2- to 5-day blocks.
• The ability to tailor examples to an Indian business context while still aligning with globally accepted best practices.
• Post-course support for participants (brief Q&A window and graded assignments).

When you reply, please mention:
• The topic(s) you can cover.
• A brief outline of your existing material.
• Any recognized certifications or notable corporate batches taught in India.

I’ll shortlist based on topic match, depth of material and prior training feedback. Looking forward to collaborating on high-impact learning experiences.

Skills: Powerpoint, Education & Tutoring, Research Writing, Business Writing, Data Science, Digital Marketing, AI Consulting, AI Development

I have a full set of customer-level records—demographics, purchase history, and web-behaviour logs—waiting to be mined. The focus is clear: I want actionable customer segmentation that can guide targeted marketing, product recommendations, and personalised onboarding journeys.

Your mission starts with solid data preparation. Please tidy the CSVs, resolve missing values and duplicates, and engineer any features you feel will sharpen the insights. From there, apply clustering or an equivalent technique you trust (K-Means, Hierarchical, RFM, or another you can justify) to uncover distinct groups in the data.

Once the segments emerge, I’ll need two concrete deliverables:

• Reproducible code: a well-commented Python notebook or R script plus a brief read-me so my in-house analyst can re-run everything without hand-holding.
• Insights pack: a concise visual report or lightweight dashboard that names each segment, explains its defining traits, and highlights the commercial opportunities it opens up.

Acceptance criteria are straightforward: the pipeline runs end-to-end on my sample data, at least three interpretable segments appear with supporting metrics, and the final artefacts reach me on time in a clean, Git-ready structure.

If extracting meaning from customer data is your wheelhouse, I’m ready to get started.

Skills: Python, Data Mining, R Programming Language, Statistical Analysis, SPSS Statistics, Data Science, Data Visualization

We are looking for an AI & ML Specialist with expertise in AI Automation, Chatbot Development, RAG systems, Machine Learning, and Python to develop and deploy intelligent AI solutions that streamline workflows and enhance business operations.

Key Responsibilities:

Develop and deploy AI/ML solutions and workflow automations.

Build and optimize custom chatbots, AI agents, and RAG-powered systems.

Design conversational AI for websites, apps, and internal tools.

Integrate AI models and automations with existing business systems.

Perform data analysis and predictive modeling for actionable insights.

Collaborate with cross-functional teams to implement AI solutions. Ensure system performance, scalability, and reliability.

Qualifications:

3+ years of experience in AI/ML, Chatbot Development, RAG systems, and Python development.

Hands-on experience with Python libraries for ML/AI (TensorFlow, PyTorch, Scikit-Learn, LangChain).

Expertise in building AI chatbots, RAG pipelines, and automation workflows.

Experience with API integrations and deployment of AI solutions.

Preferred Skills:

n8n workflow automation. Experience with vector databases (Pinecone, Chroma, FAISS, Weaviate). LLM fine-tuning and generative AI models. Cloud deployment (AWS, Azure, GCP). Benefits: Competitive compensation and project-based incentives. Flexible work and remote collaboration. Opportunity to work on cutting-edge AI/ML solutions. Collaborative and innovative environment.

How to Apply:

We welcome applications from individual freelancers and companies.
Submit your portfolio or past work showcasing AI/ML projects, Chatbot Solutions, RAG systems, Python automations, and AI agent implementations.

I’m looking to commission an end-to-end machine-learning solution that bridges physical or network security with broader technology operations. The core of the project is a single, cohesive AI that seamlessly switches context between those two worlds instead of treating them as separate silos.

Scope of intelligence
• Threat detection & prevention – real-time identification of anomalies, intrusions, policy breaches, or suspicious behavior across logs, sensors, and traffic.
• Data analysis & reporting – actionable insights, trend visualizations, and auto-generated reports that decision-makers can consume without data-science fluency.
• System optimization & automation – feedback loops that tune system performance, resource allocation, and patches/updates based on the AI’s findings.

Tech expectations
Rapid prototyping and model experimentation can live in Python (TensorFlow, PyTorch, scikit-learn—whichever suits), while performance-critical inference or low-latency modules may be rewritten in C++. I’ll host on our existing infrastructure, so clean APIs, a modular codebase, and thorough documentation are essential.

Deliverables
1. Trained models with reproducible training pipelines
2. Source code (Python & C++) and build scripts
3. REST or gRPC endpoints ready for containerization
4. Unit tests covering key logic and security edge cases
5. Deployment guide plus high-level architecture docs

Acceptance criteria
• Model accuracy/precision/latency targets agreed during kickoff are met or exceeded
• Threat-detection component generates no more than the specified false-positive rate on our validation set
• Automation routines demonstrate measurable performance gains in a controlled test

If you’ve built multi-domain AI systems before—or have a strong security analytics background—let’s talk. I’m ready to dive into datasets, constraints, and timelines as soon as you sign the NDA.

Skills: Python, Software Architecture, CUDA, Machine Learning (ML), C++ Programming, Data Visualization, Data Analysis, AI Development

We are seeking an experienced financial modeler to develop an investor-ready project finance model for SaharaLink, a proposed AI-ready data center in Morocco. The project will initially phase in 3–6 MW, with expandable capacity. The ideal candidate will have a strong background in project finance, particularly in the energy sector, and the ability to create comprehensive models that can attract investors and assess financial viability. Your expertise will be critical in structuring the financials accurately to support our funding efforts.

I need an experienced Python data-visualization user to grade the first four assignments in my course. Each task is a Jupyter Notebook built around matplotlib and seaborn. All I want back is a clear numeric or letter score for every notebook—no margin comments or extensive feedback, just straightforward grading based on what you’d expect in a standard undergraduate data-viz class.

You’ll open the notebooks, run every cell, confirm the plots render correctly, and judge code quality and completeness against the assignment prompts. When you’re done, return the notebooks untouched and include a simple summary sheet listing Assignment 1-4 with the grade you’ve assigned to each. If a notebook will not run, just flag it so I can correct it before you proceed.

Tools in play are Jupyter Notebook, Python 3, matplotlib, and seaborn. The work is for my personal learning, so there’s no formal rubric—please rely on your professional judgment. I’ll share the files right after we agree, and a quick turnaround would be ideal.

Skills: Python, Data Science, Data Visualization, Data Analysis

I have a mixed set of still photos and short video clips that need frame-accurate annotation so every person, vehicle and animal is tracked consistently from start to finish. The end goal is reliable object-tracking data, so I care as much about keeping a unique ID on each instance across frames as I do about tight, well-placed boxes or polygons.

You will receive the raw media in batches. For each image or video frame, mark every visible person, vehicle and animal, assign the correct class label, then keep the same ID on that object until it leaves the scene. I’m happy with standard output formats such as COCO JSON, YOLO TXT, or a simple CSV so long as coordinates, class names and tracking IDs are included.

Before we start the full set, I’ll provide a small sample; your annotations on that sample will serve as the acceptance test for quality and consistency. Once approved, you can move on to the remaining files and deliver them in agreed-upon milestones.

Skills: Data Science, Image Processing, Video Processing, Computer Vision, Deep Learning, Image Analysis, Object Detection, AI Development

This project aims to develop a secure, AI-assisted system for classroom sentiment and
behavior analysis using video streams. The system processes video feeds from classrooms
to infer student sentiment and engagement indicators such as attentive, neutral, disen
gaged, or distracted states. Sentiment analysis is performed at a high, non-intrusive level,
derived from visual cues including head pose, gaze direction, posture, and basic facial ex
pression categories using pre-trained computer vision models [1,2]. The system does not
perform identity recognition or individual profiling. Strong security and privacy controls
are integral to the design [3,4]. No raw video data, facial images, or biometric informa
tion are stored. All processing is conducted locally, and only anonymized, aggregated
sentiment metrics are retained

We are seeking a skilled Bot Detection Expert to analyze and score suspicious funnel traffic. You will evaluate traffic behavior, IP/ASN data, and browser fingerprints to identify potential threats. Your deliverables will include a detailed analysis, accompanying code for detection, and effective mitigations to ensure the integrity of our systems. If you have experience in this field and a keen eye for detail, we want to hear from you!

Bot detection & fingerprinting expert needed (behavior + infrastructure signals)

Goal: Identify and score suspicious/bot traffic in our web funnel, using multi-signal detection (behavior + network + browser fingerprint consistency). We want a clear bot-score approach and actionable blocking/mitigation recommendations.

Scope:

Review our traffic patterns and propose an instrumentation plan (server + client).

Define signals (behavioral, headers, IP/ASN, TLS/HTTP patterns if available, fingerprint components).

Build a bot scoring model (rules + weighted scoring).

Analyze sample logs and provide examples of suspected bot clusters with reasoning.

Provide implementation guidance and code snippets (JS + backend) plus documentation.

Include a validation plan to control false positives.

What we provide:

Sample server logs / event data (anonymized).

Funnel events and conversion definitions.

Tech stack: [fill in: Node/Python, Cloudflare, GA4, BigQuery/Postgres, etc.]

Deliverables:

Threat model + detection strategy

Signal list + scoring rubric

Analysis report with clusters/anomalies

Implementation snippets + dashboards/queries

Tuning + monitoring guide

Requirements:

Experience with bot detection / IVT / click fraud OR anti-scraping.

Ability to explain decisions and tradeoffs (false positives).

Seeking part-time marketing analytics and optimization specialist with strong quantitative skills. The role focuses on using data-driven models to identify the most effective advertising and messaging combinations.

Key responsibilities include:

Using Microsoft Excel (Solver) to optimize marketing content under clear constraints (e.g., limited ad copy, clutter tradeoffs).

Assigning and normalizing utility weights from customer preference data to maximize expected ad performance.

Modeling diminishing returns and non-linear customer response effects (e.g., over-messaging and clutter).

Conducting multivariate regression analysis to link customer needs to observed performance outcomes.

Analyzing competitor advertising and qualitative copy to identify effective messaging patterns.

Applying Python-based text analysis tools (preferred) to quantify competitor positioning and strategies.

Synthesizing insights across multiple datasets to produce clear, actionable recommendations.

Building repeatable analytical frameworks rather than one-off analyses.

Preferred background:

Experience with quantitative marketing, decision modeling, or optimization.

Familiarity with choice modeling, conjoint-style thinking, or marketing mix concepts.

Ability to translate analytical results into practical ad design guidance.

I have *.csv data file containing an X value, a Y value and a time value from a GPS. These have been taken at 1 second intervals along a route.

I would like a small .exe program to load this file into and interpolate between the times and X and Y values.

I would then like to load another file with a list of time values in (around 10-15 a second) taken in between one second real values and the program to look up and report the X and Y value which has been interpolated between points and export to a new *.csv file.

Skills: Python, Data Processing, Data Science, Data Extraction, Data Analysis, Data Integration, Data Modeling

We are looking for an AI and Machine Learning Engineer who specializes in building automation first AI solutions for real business workflows. This role is focused on delivering working systems that reduce manual effort, improve accuracy, and scale with business needs.

Key Responsibilities

Design and develop AI agents and chatbots capable of handling conversations and executing tasks.
Build RAG based architectures (LLMs connected with internal or external data sources) for reliable, context aware responses.
Develop AI automation workflows using n8n (API orchestration, triggers, and multi step logic).
Create Python based pipelines for AI, ML, and data processing.
Integrate AI systems with CRMs, databases, and third party tools.
Deploy and maintain stable, production ready AI solutions.

Required Expertise

Strong experience with Python for AI and ML development.
Hands on experience with AI agents, chatbots, and LLM integrations.
Clear understanding of RAG systems, embeddings, and vector databases.
Experience with n8n or similar automation platforms.
Ability to translate business processes into automated AI solutions.

What We Value

Practical problem solving over theory.
Ownership from planning to delivery.
Clear communication and predictable execution.